Controlled Query Evaluation with Epistemic Dependencies for Confidentiality-Preserving Query Answering

Core Concepts

The authors propose the use of epistemic dependencies to express rich data protection policies in Controlled Query Evaluation (CQE), a form of confidentiality-preserving query answering over ontologies and databases. They study the data complexity of CQE for (unions of) conjunctive queries when ontologies are specified in the Description Logic DL-LiteR, and identify conditions ensuring tractability.

Abstract

The paper introduces a novel CQE framework that uses epistemic dependencies (EDs) to express data protection policies. EDs allow for more expressive and practical forms of data protection rules compared to previous approaches.
Key highlights:

EDs enable policies that can hide the existence of certain data (e.g., admitted patients) rather than just the truth value of sentences, as in previous work.
The authors define two notions of query entailment under CQE: Skeptical Entailment (SC-entailment) and Intersection Entailment (IC-entailment).
They show that SC-entailment of Boolean Conjunctive Queries (BCQs) preserves confidentiality, but this does not hold for unions of BCQs (BUCQs). However, IC-entailment preserves confidentiality for BUCQs.
For DL-LiteR ontologies, the authors prove that SC-entailment and IC-entailment of BCQs and BUCQs are coNP-complete in data complexity.
They identify a subclass of acyclic EDs for which SC-entailment and IC-entailment of BCQs and BUCQs are first-order rewritable, and thus in AC0 in data complexity.
The results pave the way towards the practical application of this new approach to CQE.

Stats

None.

Quotes

"Rule δ2 imposes that, in the epistemic state of the user, the set of admitted patients must be empty (but this does not exclude that the user knows that some patients have been admitted)."
"Rule δ3 is saying that if a user knows that a patient has been admitted, then she must know that the patient has signed a consensus form. Thus, if a patient did not sign a consensus form, the system cannot disclose that this patient has been admitted."

Key Insights Distilled From

Controlled Query Evaluation through Epistemic Dependencies

by Gianluca Cim... at arxiv.org 05-07-2024

https://arxiv.org/pdf/2405.02458.pdf

Deeper Inquiries

How can the proposed CQE framework with epistemic dependencies be extended to handle more expressive ontology languages beyond DL-LiteR

The proposed Controlled Query Evaluation (CQE) framework with epistemic dependencies can be extended to handle more expressive ontology languages beyond DL-LiteR by incorporating more complex logical constructs and operators. One way to achieve this is by integrating higher-order logics or modal logics into the framework. These logics can provide additional expressive power to represent more intricate relationships and dependencies within the ontology and policy statements. By incorporating modal operators such as necessity and possibility, the framework can capture nuanced confidentiality requirements and access control policies.
Furthermore, extending the framework to support probabilistic reasoning can enhance its capability to handle uncertainty and probabilistic dependencies in the data. By incorporating probabilistic graphical models or Bayesian networks, the framework can provide a more comprehensive approach to confidentiality-preserving query evaluation in scenarios where probabilistic reasoning is essential.
Additionally, integrating machine learning techniques such as deep learning models can enable the framework to learn and adapt to evolving data protection policies and confidentiality requirements. By leveraging neural networks for pattern recognition and decision-making, the framework can enhance its ability to enforce complex confidentiality rules and protect sensitive information effectively.

What are the potential challenges and limitations of using epistemic dependencies for confidentiality-preserving query answering in real-world applications

While epistemic dependencies offer a powerful mechanism for expressing data protection policies in Controlled Query Evaluation (CQE), there are potential challenges and limitations in using them for confidentiality-preserving query answering in real-world applications. Some of these challenges include:

Complexity and Scalability: As the complexity of the ontology and policy statements increases, managing and reasoning with epistemic dependencies can become computationally intensive. Handling large-scale ontologies and policies may lead to scalability issues and performance bottlenecks.

Interpretability and Maintenance: Epistemic dependencies may introduce intricate logical relationships that are challenging to interpret and maintain over time. Understanding the implications of complex dependencies and ensuring their consistency with evolving data protection regulations can be demanding.

Expressiveness vs. Complexity Trade-off: While epistemic dependencies offer rich expressiveness in specifying confidentiality rules, this richness can also lead to increased complexity in query evaluation and policy enforcement. Balancing expressiveness with computational efficiency is crucial for practical implementation.

Integration with Existing Systems: Integrating epistemic dependencies into existing query evaluation systems and databases may require significant modifications and adaptations. Ensuring seamless integration and compatibility with legacy systems can be a non-trivial task.

Security and Vulnerabilities: Complex dependencies may introduce potential security vulnerabilities if not carefully designed and implemented. Adversarial attacks exploiting loopholes in the policy statements could compromise data confidentiality.

How can the notion of confidentiality preservation be further refined or generalized to capture additional security requirements beyond the indistinguishability criterion considered in this work

The notion of confidentiality preservation can be further refined or generalized to capture additional security requirements beyond the indistinguishability criterion considered in the proposed framework. Some ways to enhance and extend the concept of confidentiality preservation include:

Differential Privacy: Incorporating differential privacy mechanisms can provide stronger guarantees of privacy protection by ensuring that the presence or absence of an individual's data does not significantly impact query results. By quantifying the privacy loss in query responses, differential privacy can offer a more robust approach to confidentiality preservation.

Multi-level Security: Extending the framework to support multi-level security models can enable the enforcement of access control policies based on hierarchical security levels. By incorporating concepts such as clearance levels and need-to-know principles, the framework can address complex security requirements in environments with varying sensitivity levels.

Temporal Constraints: Introducing temporal constraints and validity periods in the policy statements can enhance the framework's ability to enforce time-sensitive confidentiality rules. By specifying when certain data can be accessed or disclosed, the framework can adapt to dynamic security requirements over time.

Fine-grained Access Control: Enhancing the granularity of access control rules to include attribute-based access control (ABAC) or role-based access control (RBAC) can provide more fine-grained control over data access. By considering specific attributes or roles in the policy statements, the framework can tailor access permissions based on detailed user characteristics.

Auditing and Compliance: Integrating auditing mechanisms and compliance checks into the framework can ensure that confidentiality preservation measures are effectively enforced and monitored. By tracking access patterns and enforcing regulatory compliance, the framework can enhance data protection and accountability.

By incorporating these advanced security measures and refining the concept of confidentiality preservation, the framework can address a broader range of security requirements and provide comprehensive data protection in diverse application scenarios.